Different external training workload models show no association with injury in competitive junior tennis players

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Deutscher übersetzter Titel:Verschiedene externe Trainingsbelastungsmodelle zeigen keinen Zusammenhang mit Verletzungen bei jungen Tennisleistungssportlern
Autor:Myers, Natalie L.; Farnsworth II, James L.; Knudson, Duane V.
Erschienen in:German journal of exercise and sport research
Veröffentlicht:52 (2022), 1, S. 97-104, Lit.
Format: Literatur (SPOLIT)
Publikationstyp: Zeitschriftenartikel
Medienart: Elektronische Ressource (online) Gedruckte Ressource
Sprache:Englisch
ISSN:2509-3150, 2509-3142
DOI:10.1007/s12662-021-00751-5
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Erfassungsnummer:PU202203001856
Quelle:BISp

Abstract des Autors

Background: A popular metric in the training load literature is the acute:chronic workload ratio (ACWR). In tennis players session rate of perceived exertion 7:28 day ACWR has been shown to be associated with injury; however, no study has examined whether this relationship is consistent with an external load variable using different ACWR time frames and mathematical calculations. The purpose of this study is to investigate different ACWRs using Cox proportional hazard models with both rolling averages and exponentially weighted moving averages (EWMA) from one external stroke load measurement. Methods: Twenty-four junior players were recruited to participate in a 34-week study, 17 were included in the final analysis. The Sony Smart Tennis Sensor was used to quantify external load in the form of swing counts, and non-contact time loss injuries were recorded. The ACWRs were calculated using two models: rolling averages and EWMA. Results: Ten players sustained injuries. The Cox regression model indicated that none of the rolling average ACWRswing count or any of the EWMA ACWRswing count models were associated with injury (P > 0.003). Conclusion: Consequently, the ACWRswing count should not be used when determining injury risk in youth tennis players. This study incorporated one load variable, but injury is multifactorial and other variables need to be considered when reducing injury likelihood.